Intelligent Vehicle Restriction Alert System
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Solution Overview
Problem
Users often forget to check vehicle restriction dates, leading to traffic violations and potential suspension of their driving licenses, as existing methods require manual queries and lack automated reminders.
Innovation Solution
A method and device that analyze user behavior data to determine vehicle restriction dates and provide intelligent alerts on a user terminal, using patterns such as terminal usage frequency and connection time to notify users of restriction days, ensuring they are aware of driving prohibitions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If manual query method is used to check vehicle restriction dates, then users can obtain restriction information, but users may forget to query and drive on restriction days causing traffic violations
Solution Approach 1:
The system performs preliminary actions by automatically analyzing user behavior data to predict when the user intends to drive, and proactively sends alert notifications before the scheduled driving time. This eliminates the need for users to manually query restriction dates and ensures they are reminded in advance, preventing traffic violations while maintaining ease of use.
Solution Approach 2:
The system enables self-service by automatically monitoring user behavior patterns, determining intended driving times, and sending alerts without requiring any manual intervention from users. The system serves itself by using its own collected data to generate and send notifications, ensuring compliance while minimizing user effort.
2Reliability
If automated alert system is implemented to notify users of restriction dates, then traffic violation risk is reduced, but system complexity increases
Solution Approach 1:
The system uses the user terminal as an intermediary to receive and display alert notifications. Instead of requiring a complex dedicated alert device, the system leverages the existing user terminal (smartphone, tablet, or in-vehicle display) to deliver notifications, thereby reducing overall system complexity while maintaining effective alert delivery.
Solution Approach 2:
The system determines alert timing by analyzing changes in user behavior parameters such as terminal usage patterns, location data, and historical driving behavior. By monitoring parameter changes rather than requiring fixed user input, the system achieves automated, context-aware alerting with relatively simple implementation logic.
3Measurement precision
If user behavior data is analyzed to determine driving intent, then alert timing accuracy is improved, but data processing complexity increases
Solution Approach 1:
The system applies partial action by focusing on analyzing only the most relevant user behavior parameters that strongly correlate with driving intent, such as terminal usage patterns and location changes during typical driving hours. Rather than comprehensively analyzing all possible behavior data, the system selectively processes key parameters to achieve sufficient accuracy with reduced computational complexity.
4Loss of information
If alert notifications are sent to user terminal, then user awareness of restriction dates is improved, but energy consumption increases
Solution Approach 1:
The system uses periodic action by sending alert notifications only at specific, predetermined intervals before the user's scheduled driving time, rather than continuously monitoring and notifying. This periodic approach ensures users receive necessary information to maintain awareness while minimizing unnecessary energy consumption from frequent or continuous notifications.
Data Source
AI summary
The disclosure provides method and device for providing alert information on a vehicle and storage medium. The method includes analyzing user behavior data of a certain period of time in association with a user terminal to obtain vehicle restriction dates during the certain period of time, determining a vehicle restriction pattern based on the vehicle restriction dates, determining a new vehicle restriction date based on the vehicle restriction pattern, and providing the alert information on the vehicle to the user terminal based on the new vehicle restriction date. In the disclosure, a user terminal analyzes user behavior data automatically and acquires a user restriction pattern, and derives a vehicle restriction date according to the user restriction pattern and intelligently alerts the user to vehicle restriction when the above vehicle restriction date is upcoming.


